Dr. Dayeong An | Engineering | Women Researcher Award

Dr. Dayeong An, Medical College of Wisconsin, United States

Dr. Dana (Dayeong) An is a Postdoctoral Fellow in the Department of Radiology at Northwestern University with a strong interdisciplinary background in biomedical engineering, computational sciences, and statistics. Her research focuses on machine learning and probabilistic modeling for multimodal biomedical data integration, particularly in neurovascular and cardiac imaging. She has developed advanced AI frameworks for stroke outcome prediction, perfusion analysis, and cardiac strain estimation. With multiple peer-reviewed publications and awards, Dr. An brings expertise in deep learning, medical image processing, and translational AI for precision medicine.

Profile

ORCID

🎓 Early Academic Pursuits

Dr. Dana (Dayeong) An’s academic journey is rooted in a solid foundation of mathematics, statistics, and computational sciences. She began her higher education at Minnesota State University, earning a B.S. in Mathematics with a minor in Economics in 2012. Her strong mathematical background laid the groundwork for advanced study, leading her to pursue dual M.S. degrees in Mathematics and Statistics (2014) and Computational Sciences (2018). These degrees reflect a growing interest in data analysis, modeling, and algorithmic thinking—skills that would become central to her future research. Her academic path culminated in a Ph.D. in Biomedical Engineering from the Medical College of Wisconsin in 2024. During her doctoral training, Dr. An fused her analytical skills with biomedical applications, working at the intersection of medical imaging and machine learning. Her education reflects a rare combination of quantitative rigor and domain-specific insight, enabling her to tackle complex problems in healthcare and precision medicine.

🧠 Professional Endeavors

Dr. An currently serves as a Postdoctoral Fellow in the Department of Radiology at Northwestern University, where she applies advanced machine learning techniques to neurovascular and cardiac imaging data. Her professional roles have spanned research, teaching, and clinical applications. At the Medical College of Wisconsin, she worked as a Research Assistant, refining deep learning algorithms for myocardial strain analysis, MRI-based diagnostics, and experimental studies on cardiotoxicity in animal models. Earlier in her career, she served as an Adjunct Professor and Teaching Assistant at multiple institutions, including Marquette University, Globe University, and South Central College, where she taught a variety of math and statistics courses. This teaching experience showcases her commitment to education and her ability to communicate complex topics to diverse audiences.

🧪 Contributions and Research Focus

Dr. An’s research is centered on machine learning and probabilistic modeling for multimodal biomedical data integration. Her contributions span multiple domains:

• Neurovascular Imaging: She has developed frameworks using Bayesian priors and transformer models to estimate physiological parameters from perfusion MRI data. She also works with large-scale databases such as NVQI-QOD to predict stroke outcomes and recurrence risks in intracranial atherosclerotic disease (ICAD).

• Cardiac MRI and Strain Analysis: Dr. An fine-tuned U-Net and GAN architectures to automate strain generation and displacement field analysis from cine MRI images. These tools enhance early detection of cardiotoxicity and improve diagnostic accuracy.

• Image Processing and Simulation: She built deep learning-based deformable registration tools to reduce motion artifacts in angiography and improve vascular fidelity. Additionally, she contributed to differentiable projection modeling for fluoroscopic pose estimation.

• Translational AI: Her work aims to bridge the gap between algorithm development and clinical implementation, with models designed for real-time, patient-specific analysis.

Her research is not only technical but also translational, addressing real-world challenges in healthcare delivery and diagnostics.

🏆 Accolades and Recognition

Dr. An has received numerous honors for her research excellence and academic contributions:

• Poster Competition Winner at Marquette University and the Medical College of Wisconsin.

• Scholarship and Travel Grants from prestigious societies such as the Global Cardio Oncology Summit, ISMRM, and Marquette University.

• Kayoko Ishizuka Award and Graduate Student Association Awards at MCW.

• Recognition for conference presentations at RSNA, ISMRM, SCMR, and ASNR.

Her work has been published in well-regarded journals including Radiology and Oncology, Journal of Imaging Informatics in Medicine, and Tomography, reflecting her influence across multiple disciplines.

🌍 Impact and Influence

Dr. An’s interdisciplinary expertise positions her as a valuable contributor to both the academic and clinical communities. Her collaborations with leading institutions such as Cleveland Clinic and Purdue University demonstrate the broader impact of her research. Whether improving stroke outcome prediction or refining cardiac diagnostics, her contributions are making real-world differences in how clinicians approach patient care. She is also actively involved in professional societies like RSNA, ISMRM, IEEE, and the American Statistical Association, fostering knowledge exchange and staying at the forefront of innovation.

🌱 Legacy and Future Contributions

Looking ahead, Dr. An aspires to expand her impact by continuing to develop explainable, reliable, and patient-specific AI tools for medical imaging. Her future work will likely delve deeper into probabilistic deep learning, longitudinal outcome modeling, and integrated diagnostics using multi-modal data sources such as imaging, genomics, and electronic health records. She is poised to be a leader in translational AI, driving innovations that not only push the boundaries of computational medicine but also enhance patient outcomes and healthcare efficiency.

🔗 Final Thoughts

Dr. Dana (Dayeong) An exemplifies a new generation of biomedical engineers—fluent in mathematics, passionate about clinical impact, and committed to advancing the future of precision medicine through data-driven innovation. Her legacy is being built at the nexus of technology, healthcare, and humanity.

📄 Publication Top Notes

Radiation-Induced Cardiotoxicity in Hypertensive Salt-Sensitive Rats: A Feasibility Study

Author: Dayeong An; Alison Kriegel; Suresh Kumar; Heather Himburg; Brian Fish; Slade Klawikowski; Daniel Rowe; Marek Lenarczyk; John Baker; El-Sayed Ibrahim

Journal: Life

Year: 2025

Elucidating Early Radiation-Induced Cardiotoxicity Markers in Preclinical Genetic Models Through Advanced Machine Learning and Cardiac MRI

Author: Dayeong An; El-Sayed Ibrahim

Journal: Journal of Imaging

Year: 2024